CN111904079A - Worker health monitoring method based on intelligent safety helmet - Google Patents
Worker health monitoring method based on intelligent safety helmet Download PDFInfo
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- A—HUMAN NECESSITIES
- A42—HEADWEAR
- A42B—HATS; HEAD COVERINGS
- A42B3/00—Helmets; Helmet covers ; Other protective head coverings
- A42B3/04—Parts, details or accessories of helmets
- A42B3/0406—Accessories for helmets
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- A—HUMAN NECESSITIES
- A42—HEADWEAR
- A42B—HATS; HEAD COVERINGS
- A42B3/00—Helmets; Helmet covers ; Other protective head coverings
- A42B3/04—Parts, details or accessories of helmets
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- A42B3/046—Means for detecting hazards or accidents
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
- A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
- A61B5/0022—Monitoring a patient using a global network, e.g. telephone networks, internet
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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- A61B5/02438—Detecting, measuring or recording pulse rate or heart rate with portable devices, e.g. worn by the patient
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- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/14542—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring blood gases
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
- A61B5/6803—Head-worn items, e.g. helmets, masks, headphones or goggles
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- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
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- A61B2503/00—Evaluating a particular growth phase or type of persons or animals
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Abstract
The invention discloses a worker health monitoring method based on an intelligent safety helmet. The method comprises four parts, namely an intelligent safety helmet, a health data module, a specially-made analysis module and a state management module. The working principle of the method is as follows: (1) the intelligent safety helmet with the brain wave and blood oxygen heart rate module collects physical sign information of workers in real time and uploads data; (2) performing real-time data analysis on the physical sign information data of the workers, and calculating fatigue, attention concentration, blood oxygen content and heart rate indexes of the workers; (3) and recording the health state of the worker and giving a prompt and early warning to the worker when the health index exceeds a threshold value. The intelligent safety helmet is designed in the form and the using mode of the intelligent safety helmet, and a health state monitoring method specially used for workers during working is developed by applying circuits such as brain wave acquisition and the like, so that monitoring, analysis and feedback of blood oxygen, heart rate, fatigue and attention indexes of the workers are realized, and risk early warning can be actively carried out on the basis of the health condition of the workers.
Description
Technical Field
The invention belongs to the field of health management, and particularly relates to a worker health monitoring method based on an intelligent safety helmet.
Background
In a work area with a high risk level, such as a factory, a construction site and the like, the health risk of workers is high, so that the workers are required to wear safety helmets to provide protection for safety, and the intelligent safety helmets and monitoring systems on the market can provide information of the positions, environments and the like of the workers at present.
The existing intelligent safety helmet and the existing monitoring system can only passively resist and prompt external environmental risks, and only serve as a temporary last barrier for risks, so that active monitoring and management on the physical health state of workers cannot be realized.
Disclosure of Invention
The invention aims to provide a worker health monitoring method based on an intelligent safety helmet, and aims to solve the problem that the existing intelligent safety helmet and monitoring method in the market cannot monitor the health state of a worker and prompt internal risks of the body. The method is designed based on the characteristics of the intelligent safety helmet, the health of workers is monitored by combining a non-invasive brain wave acquisition circuit and a brain wave algorithm, the brain waves, the blood oxygen content and the heart rate indexes of the workers wearing the intelligent safety helmet can be monitored in real time, the fatigue and the attention condition of the workers are analyzed, active feedback is carried out when the health indexes of the workers are abnormal, and early warning is carried out on health risks.
In order to achieve the above purpose, the invention provides the following technical scheme: a worker health monitoring method based on an intelligent safety helmet. The method comprises the steps of sign data acquisition, transmission, storage, analysis, monitoring and early warning prompting based on the intelligent safety helmet, wherein the steps comprise an intelligent safety helmet, a health data module, a specially-made analysis module and a state management module. The method comprises the steps of sign data acquisition, transmission, storage, analysis, monitoring and early warning prompt based on the intelligent safety helmet:
the first step is as follows: recording an intelligent safety cap connection code and information of a worker wearing the intelligent safety cap connection code in a state management module of the server, and starting and wearing the intelligent safety cap;
the second step is that: the intelligent safety helmet collects physical sign data of brain waves, heart rate and blood oxygen content of workers and transmits the physical sign data to a health data module serving the intelligent safety helmet in real time through a wireless network;
the third step: a special analysis module synchronizes and analyzes the physical sign data in real time and judges the fatigue degree and the attention concentration degree of workers;
the fourth step: the state management module monitors and records fatigue, attention, blood oxygen and heart rate indexes of workers and updates the health state of the workers in real time;
the fifth step: when the index of the health state reaches beyond the reasonable threshold value, the server feeds back a health abnormal instruction to the intelligent safety helmet through the health data module, the intelligent safety helmet buzzes, and risk prompt and early warning are carried out on workers.
Preferably, the specific processes of the sign data acquisition, transmission and storage in the first step and the second step are as follows:
the first step is as follows: inputting a connection code of the intelligent safety helmet in a state management module of the server, and filling in identity information of a company, a project, a name, a telephone and the like of a corresponding worker of the intelligent safety helmet;
the second step is that: turning on a switch of the intelligent safety helmet and wearing the intelligent safety helmet, wherein the intelligent safety helmet acquires brain wave, heart rate and blood oxygen content information of workers;
the third step: the brain wave signals, the heart rate and the blood oxygen data are uploaded to a health data module of the server in real time through a wireless network;
the fourth step: the health data module receives physical sign data of workers, stores the physical sign data according to identity information of the workers and transmits the physical sign data to the special analysis module in real time.
Preferably, the third step of performing real-time physical sign data analysis specifically comprises the following steps:
the first step is as follows: a specially-made analysis module analyzes time domains and frequency domains of brain wave signals corresponding to fatigue and attention, extracts signal characteristic parameters and establishes a database;
the second step is that: establishing a machine learning model through a random forest algorithm, grading the fatigue degree and attention indexes corresponding to the signal characteristic parameters in the database and converting the grades into score values;
the third step: the brain wave data in the real-time synchronous health data module is subjected to noise and interference removal through a regression method, a self-adaptive filtering method and an independent component analysis method;
the fourth step: carrying out power spectral density and frequency spectrum analysis on the time domain and the frequency domain of the de-noised electroencephalogram data, and extracting signal characteristic parameters;
the fifth step: and judging score values corresponding to the fatigue degree and the attention level of the worker in real time by comparing the classified and graded signal characteristic parameters in the database.
Preferably, the fourth step of monitoring the health status of the worker physical sign data includes the following specific steps:
the first step is as follows: the state management module collects the connection codes of the intelligent safety helmet and the identity information of workers, and synchronizes the fatigue, the attention level and the blood oxygen heart rate data in real time;
the second step is that: and updating data with a specially-made analysis module and a health data module in real time, and recording the health state data of the latest workers.
Preferably, the specific process of the step of performing early warning prompt when the health status index of the fifth step is beyond a reasonable threshold is as follows:
the first step is as follows: setting a health index score threshold value in a state management module;
the second step is that: when the real-time updated worker health index exceeds the set threshold, the state management module sends a health abnormal instruction to the health data module;
the third step: the health data module transmits the health abnormal instruction to the intelligent safety helmet through a wireless network;
the fourth step: the intelligent safety helmet starts the buzzer to prompt and warn health risks of workers.
Compared with the prior art, the invention has the beneficial effects that:
(1) the system is designed based on the characteristics of the intelligent safety helmet, realizes the real-time acquisition of brain wave signals, blood oxygen content and heart rate indexes, and provides basic data information for the health state monitoring of workers;
(2) the health data module designed by the system remotely receives physical sign data of workers for classified storage management by taking a wireless network interface as a transmission mode, so that the data use efficiency is effectively improved;
(3) the specially-made data analysis module of the system provides a function of monitoring the fatigue degree and the concentration degree of attention based on brain wave signals, increases the latitude of the health state of monitoring workers, and better provides protection for the health of the workers;
(4) the health management module designed by the system can set a threshold value of the health state index, monitors the self health state of workers through real-time data synchronization, and realizes active early warning of the health state exceeding the threshold value.
Drawings
FIG. 1 is a flow chart of an application of a worker health monitoring method based on an intelligent safety helmet according to the present invention;
FIG. 2 is a schematic structural diagram of an intelligent safety helmet based on a worker health monitoring method of the intelligent safety helmet;
FIG. 3 is a schematic flow chart of sign data acquisition, transmission and storage of a worker health monitoring method based on an intelligent safety helmet;
FIG. 4 is a schematic flow chart illustrating the brain wave sign data analysis step of the worker health monitoring method based on the intelligent safety helmet of the present invention;
FIG. 5 is a flowchart of the application of worker health monitoring and early warning in the worker health monitoring method based on the intelligent safety helmet of the present invention;
fig. 6 is a schematic diagram illustrating the principle of the worker health monitoring method based on the intelligent safety helmet.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1-2, the present invention provides a technical solution: the utility model provides a workman health monitoring method based on intelligent safety helmet, includes a set of sign data acquisition based on intelligent safety helmet, transmission, storage, analysis, control and early warning suggestion's step, specifically is in this embodiment:
the first step is as follows: recording an intelligent safety cap connection code and information of a worker wearing the intelligent safety cap connection code in a state management module of the server, and starting and wearing the intelligent safety cap;
the second step is that: the intelligent safety helmet collects physical sign data of brain waves, heart rate and blood oxygen content of workers and transmits the physical sign data to a health data module serving the intelligent safety helmet in real time through a wireless network;
the third step: a special analysis module synchronizes and analyzes the physical sign data in real time and judges the fatigue degree and the attention concentration degree of workers;
the fourth step: the state management module monitors and records fatigue, attention, blood oxygen and heart rate indexes of workers and updates the health state of the workers in real time;
the fifth step: when the index of the health state reaches beyond the reasonable threshold value, the server feeds back a health abnormal instruction to the intelligent safety helmet through the health data module, the intelligent safety helmet buzzes, and risk prompt and early warning are carried out on workers.
In this embodiment, preferably, as shown in fig. 3, the specific flow of the sign data acquisition, transmission and storage step in the first step and the second step is as follows:
the first step is as follows: inputting a connection code of the intelligent safety helmet in a state management module of the server, and filling in identity information of a company, a project, a name, a telephone and the like of a corresponding worker of the intelligent safety helmet;
the second step is that: turning on a switch of the intelligent safety helmet and wearing the intelligent safety helmet, wherein the intelligent safety helmet acquires brain wave, heart rate and blood oxygen content information of workers;
the third step: the brain wave signals, the heart rate and the blood oxygen data are uploaded to a health data module of the server in real time through a wireless network;
the fourth step: the health data module receives physical sign data of workers, stores the physical sign data according to identity information of the workers and transmits the physical sign data to the special analysis module in real time.
In this embodiment, preferably, as shown in fig. 4, the specific process of the third step of performing real-time physical sign data analysis includes:
the first step is as follows: a specially-made analysis module analyzes time domains and frequency domains of brain wave signals corresponding to fatigue and attention, extracts signal characteristic parameters and establishes a database;
the second step is that: establishing a machine learning model through a random forest algorithm, grading the fatigue degree and attention indexes corresponding to the signal characteristic parameters in the database and converting the grades into score values;
the third step: the brain wave data in the real-time synchronous health data module is subjected to noise and interference removal through a regression method, a self-adaptive filtering method and an independent component analysis method;
the fourth step: carrying out power spectral density and frequency spectrum analysis on the time domain and the frequency domain of the de-noised electroencephalogram data, and extracting signal characteristic parameters;
the fifth step: and judging score values corresponding to the fatigue degree and the attention level of the worker in real time by comparing the classified and graded signal characteristic parameters in the database.
In this embodiment, preferably, as shown in fig. 6, the specific process of the fourth step of monitoring the health status of the worker physical sign data includes:
the first step is as follows: the state management module collects the connection codes of the intelligent safety helmet and the identity information of workers, and synchronizes the fatigue, the attention level and the blood oxygen heart rate data in real time;
the second step is that: and updating data with a specially-made analysis module and a health data module in real time, and recording the health state data of the latest workers.
In this embodiment, preferably, as shown in fig. 5, the concrete procedure of the fifth step of performing the early warning prompt when the health status index is out of the reasonable threshold is as follows:
the first step is as follows: setting a health index score threshold value in a state management module;
the second step is that: when the real-time updated worker health index exceeds the set threshold, the state management module sends a health abnormal instruction to the health data module;
the third step: the health data module transmits the health abnormal instruction to the intelligent safety helmet through a wireless network;
the fourth step: the intelligent safety helmet starts the buzzer to prompt and warn health risks of workers.
The invention judges the reference parameter range of fatigue degree and attention concentration degree based on electroencephalogram data:
fatigue reference range [0 to 100 ]:
fatigue: 0 to 19;
abundant: 20 to 100;
attention concentration reference range [0 to 100 ]:
the attention control is strong: 0 to 59;
attention control is normal: 60 to 90;
attention control is weak: 91 to 100.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (5)
1. A worker health monitoring method based on an intelligent safety helmet is characterized by comprising the following steps: including sign data acquisition, transmission, storage, analysis, control and early warning suggestion step, sign data acquisition, transmission, storage, analysis, control and early warning suggestion step is:
the first step is as follows: recording an intelligent safety cap connection code and information of a worker wearing the intelligent safety cap connection code in a state management module of the server, and starting and wearing the intelligent safety cap;
the second step is that: the intelligent safety helmet collects physical sign data of brain waves, heart rate and blood oxygen content of workers and transmits the physical sign data to a health data module serving the intelligent safety helmet in real time through a wireless network;
the third step: a special analysis module synchronizes and analyzes the physical sign data in real time and judges the fatigue degree and the attention concentration degree of workers;
the fourth step: the state management module monitors and records fatigue, attention, blood oxygen and heart rate indexes of workers and updates the health state of the workers in real time;
the fifth step: when the index of the health state reaches beyond the reasonable threshold value, the server feeds back a health abnormal instruction to the intelligent safety helmet through the health data module, the intelligent safety helmet buzzes, and risk prompt and early warning are carried out on workers.
2. The intelligent safety helmet-based worker health monitoring method according to claim 1, wherein: the specific processes of the sign data acquisition, transmission and storage steps in the first step and the second step are as follows:
the first step is as follows: inputting a connection code of the intelligent safety helmet in a state management module of the server, and filling in identity information of a company, a project, a name, a telephone and the like of a corresponding worker of the intelligent safety helmet;
the second step is that: turning on a switch of the intelligent safety helmet and wearing the intelligent safety helmet, wherein the intelligent safety helmet acquires brain wave, heart rate and blood oxygen content information of workers;
the third step: the brain wave signals, the heart rate and the blood oxygen data are uploaded to a health data module of the server in real time through a wireless network;
the fourth step: the health data module receives physical sign data of workers, stores the physical sign data according to identity information of the workers and transmits the physical sign data to the special analysis module in real time.
3. The intelligent safety helmet-based worker health monitoring method according to claim 1, wherein: the third step of real-time physical sign data analysis comprises the following specific procedures:
the first step is as follows: a specially-made analysis module analyzes time domains and frequency domains of brain wave signals corresponding to fatigue and attention, extracts signal characteristic parameters and establishes a database;
the second step is that: establishing a machine learning model through a random forest algorithm, grading the fatigue degree and attention indexes corresponding to the signal characteristic parameters in the database and converting the grades into score values;
the third step: the brain wave data in the real-time synchronous health data module is subjected to noise and interference removal through a regression method, a self-adaptive filtering method and an independent component analysis method;
the fourth step: carrying out power spectral density and frequency spectrum analysis on the time domain and the frequency domain of the de-noised electroencephalogram data, and extracting signal characteristic parameters;
the fifth step: and judging score values corresponding to the fatigue degree and the attention level of the worker in real time by comparing the classified and graded signal characteristic parameters in the database.
4. The intelligent safety helmet-based worker health monitoring method according to claim 1, wherein: the fourth step of monitoring the health status of the worker sign data comprises the following specific steps:
the first step is as follows: the state management module collects the connection codes of the intelligent safety helmet and the identity information of workers, and synchronizes the fatigue, the attention level and the blood oxygen heart rate data in real time;
the second step is that: and updating data with a specially-made analysis module and a health data module in real time, and recording the health state data of the latest workers.
5. The intelligent safety helmet-based worker health monitoring method according to claim 1, wherein: and when the health state index reaches the outside of the reasonable threshold value, the concrete process of the step of carrying out early warning prompt is as follows:
the first step is as follows: setting a health index score threshold value in a state management module;
the second step is that: when the real-time updated worker health index exceeds the set threshold, the state management module sends a health abnormal instruction to the health data module;
the third step: the health data module transmits the health abnormal instruction to the intelligent safety helmet through a wireless network;
the fourth step: the intelligent safety helmet starts the buzzer to prompt and warn health risks of workers.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113990477A (en) * | 2021-10-20 | 2022-01-28 | 上海轻迅信息科技有限公司 | Big data intelligent health monitoring system based on cloud platform |
| CN114469024A (en) * | 2021-12-23 | 2022-05-13 | 广东建采网科技有限公司 | Construction worker safety early warning method and system based on smart band |
| CN115294726A (en) * | 2022-07-08 | 2022-11-04 | 国网浙江省电力有限公司电力科学研究院 | Safety control method for electric power operation and safety helmet |
| CN116343449A (en) * | 2023-02-09 | 2023-06-27 | 清华大学 | Safety monitoring and early warning method, device and system for construction site |
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